Secretary Wright visited PNNL's campus in Richland, Washington, late last year to meet with innovators in chemistry, biology, computing, and more.

Distributed science is thriving at PNNL, where scientists share data and collaborate with researchers around the world to increase the impact of the work.

A closed-loop workflow brings together digital and physical frameworks to advance high-throughput experimentation on redox-active molecules in flow batteries.

This achievement earned DIMPLES a Best Paper award at the ACM International Conference on Supercomputing 2025.

Three research teams led by PNNL organizers achieve journal publications following the Mathematics Research Communities program.

Expanding the nation’s largest wind power plant time series database; helping grid planners navigate a resilient energy future with better data.

More than 25,000 participants from industry, government, academia, and the public attended the event.

PNNL's E-COMP initiative is helping unleash American energy innovation with advanced theories, models, and software tools to better operate power systems that rely heavily on high-speed power electronic control.

PNNL researchers have published their paper, “Introducing Molecular Hypernetworks for Discovery in Multidimensional Metabolomics Data,” in the Journal of Proteome Research.

Klickitat Valley Health's fuel cell and microgrid project boosts rural healthcare, enhancing energy resilience and sustainability for social equity.

Three PNNL-supported projects are at the forefront of developing advanced data analytics technologies to enhance the U.S. power grid’s reliability, resilience, and affordability.

The Grid Storage Launchpad dedication event was attended by leaders in grid and transportation energy storage, battery innovation, and industry stakeholders working to transform America’s energy system.

Erich Hsieh, Deputy Assistant Secretary for OE’s Energy Storage Division, shared insights about the Grid Storage Launchpad and energy storage innovations .

Researchers created a methodology to design custom network topologies that improve the execution time for scientific applications.

Researchers unveil user-friendly software to keep complex projects on budget and on schedule.

PNNL researchers present challenges and opportunities for fusing graph neural networks with deep reinforcement learning.

PNNL researchers outline open problems in different scientific areas in the Journal of Combinatorics.

Methods review suggests ways to use artificial intelligence and machine learning to handle missing data when integrating two or more omics approaches.

To thwart pathogens, researchers in the epidemiology field of infectious disease (ID) prediction are continuously trying to forecast when, where, and how an ID event will occur.

PNNL joint appointee Auroop Ganguly uses data science to study the impacts of climate change.